Instructions to use dfurman/Llama-2-7B-Instruct-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dfurman/Llama-2-7B-Instruct-v0.1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "dfurman/Llama-2-7B-Instruct-v0.1") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dfurman/Llama-2-7B-Instruct-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 269 MB
-
https://huggingface.co/dfurman/Llama-2-7B-Instruct-v0.1/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dfurman/Llama-2-7B-Instruct-v0.1/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dfurman/Llama-2-7B-Instruct-v0.1/resolve/main/adapter_model.bin
269 MB
- Xet hash:
- ff34e2237f1718eb23c0f27263581428111e8834555f225cb5bd0c15a53cbaf5
- Size of remote file:
- 269 MB
- SHA256:
- fd6d9c4e3d74f979c401032ba159bbf763bae4055bf0fff54c6a98ad4b0d5ad6
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